作物杂志,2024, 第3期: 13–22 doi: 10.16035/j.issn.1001-7283.2024.03.003

• 遗传育种·种质资源·生物技术 • 上一篇    下一篇

不同谷子品种喷施咪唑啉酮除草剂后的转录组分析

宋慧1(), 王涛2, 邢璐1, 刘俊芳1, 张扬1, 刘金荣1, 陈红旗1(), 冯佰利3   

  1. 1安阳市农业科学院,455000,河南安阳
    2安阳工学院生物与食品工程学院,455000,河南安阳
    3西北农林科技大学农学院/旱区作物逆境生物学国家重点实验室,712100,陕西杨凌
  • 收稿日期:2023-01-27 修回日期:2023-03-30 出版日期:2024-06-15 发布日期:2024-06-18
  • 通讯作者: 陈红旗,研究方向为谷子遗传育种与栽培技术,E-mail:aychq@126.com
  • 作者简介:宋慧,研究方向为谷子资源与遗传育种,E-mail:837181622@qq.com
  • 基金资助:
    国家现代农业产业技术体系建设专项(CARS-06-14.5-B25);河南省青年人才托举工程项目(2021HYTP035);河南省现代农业产业体系建设专项(HARS-22-04-Z1);河南省自然科学基金(222300420101)

Transcriptome Analysis of Different Foxtail Millet (Setaria italica L.) Varieties Treated with Imazapic Herbicide

Song Hui1(), Wang Tao2, Xing Lu1, Liu Junfang1, Zhang Yang1, Liu Jinrong1, Chen Hongqi1(), Feng Baili3   

  1. 1Anyang Academy of Agricultural Sciences, Anyang 455000, Henan, China
    2College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
    3College of Agriculture, Northwest Agriculture and Forestry University / State Key Laboratory of Crop Stress Biology in Arid Areas, Yangling 712100, Shaanxi, China
  • Received:2023-01-27 Revised:2023-03-30 Online:2024-06-15 Published:2024-06-18

摘要:

咪唑啉酮类除草剂能有效防治谷子田的单、双子叶杂草,为探究谷子对咪唑啉酮类除草剂抗性的分子机制,于抗性品种(R)和敏感品种(S)出苗后15 d均匀地喷洒甲咪唑烟酸,通过高通量RNA-Seq测序分析抗性和敏感谷子品种中差异表达的基因和代谢途径。结果表明,2个品种在除草剂处理后,与光合作用和代谢途径相关的基因均被下调,特别是在敏感品种中下调更为显著。同样,敏感品种在除草剂处理后,与脂肪酸延伸相关基因表达也显著下调。5个随机选择基因的实时定量PCR(qRT-PCR)的结果与深度测序的结果一致。上述相关基因可能在谷子对咪唑啉酮类除草剂的抗性中起重要作用。

关键词: 咪唑啉酮, 转录组, 差异表达基因, 谷子

Abstract:

Imidazolinone herbicides can effectively control monocotyledonous and dicotyledonous weeds in foxtail millet fields. In order to explore the molecular mechanism of millet resistance to imidazolinone herbicides, after the emergence of resistant varieties (R) and sensitive varieties (S) differentially expressed genes and metabolic pathways in resistant and susceptible foxtail millet cultivars were analyzed by high-throughput RNA-Seq sequencing after 15 d of uniform spraying with methamphetamine nicotinic acid. The results showed that genes related to photosynthesis and metabolic pathways were down-regulated after herbicide treatment in both cultivars. However, the down-regulation was more significant in the sensitive cultivar. Similarly, fatty acid elongation genes were significantly down-regulated after herbicide treatment in the sensitive cultivar. Quantitative real-time PCR (qRT-PCR) results of five candidate genes showed excellent agreement with those deep sequencing. These genes may play an important role in the imidazolinone herbicide resistance.

Key words: Imazapic, Transcriptome, Differentially expressed genes, Foxtail millet

表1

qRT-PCR所用引物

引物名称
Primer name
引物序列
Primer sequence (5′-3′)
SiACTIN7-F GGCAAACAGGGAGAAGATGA
SiACTIN7-R GAGGTTGTCGGTAAGGTCACG
LOC101765996-F CATTCACAGCCTGAGGTGTTTCC
LOC101765996-R CCATCTCCGACATCTCGCATT
LOC101784847-F GACATCCCGGAGGTGCTCAA
LOC101784847-R CGTCAGGCTCGGCATTCAA
LOC101759205-F AGACATCACCGACCTGTTCCAA
LOC101759205-R GCCCAGCACTTGTTCTCACG
LOC101765796-F ACGCCATCAACTTCCCCATC
LOC101765796-R GCCTTGTAGACGACGACCCA
LOC101782898-F AGACAACCGAAAATCAGCAGACAG
LOC101782898-R TGCCCTCAGGTATGCCCAGT

表2

谷子转录组数据

样本
Sample
有效数据
Clean reads
映射数据
Mapped reads
映射率
Mapped rate (%)
唯一映射率
Unique mapped rate (%)
GC
(%)
Q20
(%)
Q30
(%)
R0_1 35 066 474 31 574 750 90.04 87.36 56.00 96.67 91.78
R0_2 27 620 386 25 642 394 92.84 89.43 54.00 97.23 92.65
R0_3 30 454 968 28 403 582 93.26 89.87 55.50 97.36 92.86
S0_1 32 637 848 29 758 054 91.18 87.40 55.00 96.75 92.06
S0_2 32 213 222 29 246 420 90.79 86.69 55.00 96.76 92.11
S0_3 30 212 562 27 707 582 91.71 86.30 54.50 96.91 92.26
RT_1 41 040 330 38 384 804 93.53 90.81 53.50 97.48 93.26
RT_2 32 272 636 29 688 540 91.99 88.97 54.00 97.19 92.74
RT_3 31 474 482 28 009 464 88.99 86.24 53.50 96.55 91.90
ST_1 31 395 192 28 837 638 91.85 89.42 53.00 96.82 92.31
ST_2 32 216 306 29 179 166 90.57 87.82 53.50 96.92 92.42
ST_3 38 151 776 35 326 060 92.59 89.61 53.00 97.26 92.91
WRT_1 30 168 990 26 748 998 88.66 82.49 54.00 96.40 91.63
WRT_2 41 280 980 38 641 026 93.60 89.58 55.00 97.75 93.49
WRT_3 33 018 182 30 868 352 93.49 89.25 55.00 97.66 93.26
WST_1 42 602 542 38 785 788 91.04 87.82 55.50 97.80 93.64
WST_2 38 116 254 33 591 880 88.13 84.78 55.50 97.78 93.60
WST_3 45 776 540 41 381 022 90.40 87.53 56.50 97.85 93.66

表3

差异表达基因的数量

比较组
Comparison group
DEG数
DEG number
上调
Up-regulated
下调
Down-regulated
RT vs R0 1413 983 430
ST vs S0 7453 3566 3887
RT vs WRT 743 615 128
ST vs WST 5298 2396 2902
WRT vs R0 186 71 115
WST vs S0 920 453 467

图1

除草剂和水处理0 h和48 h后抗性(a)和敏感(b)品种差异表达基因的维恩图

图2

处理后谷子差异表达基因的GO分类

图3

20条KEGG通路显著富集的散点图 (a) RT vs WRT;(b) ST vs WST。富集因子是该通路注释的DEG数与该通路注释的所有基因数的比值。更大的富集因子意味着更大的密集度。q值是修正后的p值,取值范围在0到1之间。q值越低,富集越显著。

图4

支链氨基酸合成相关差异表达基因热图分析 条形图表示热图中每个基因表达水平(log2 TPM)。基因的表达水平用不同的颜色表示。红色表示高表达,蓝色表示低表达。

图5

光合相关DEG热图分析 (a) 与天线蛋白相关的DEG;(b) 与光系统相关的DEG;(c) 与碳固定相关的DEG。条形图表示热图中每个基因表达水平(log2 TPM)。基因的表达水平用不同的颜色表示。红色表示高表达,蓝色表示低表达。下同。

图6

涉及代谢途径的DEG的热图分析 条形图表示热图中每个基因表达水平(log2 TPM)。

图7

超长链脂肪酸延长酶相关DEG的热图分析

图8

RNA-Seq测序数据的qRT-PCR分析

[1] 刁现民. 基础研究提升传统作物谷子和黍稷的科研创新水平. 中国农业科学, 2016, 49(17):3260-3262.
[2] Muthamilarasan M, Prasad M. Advances in Setaria genomics for genetic improvement of cereals and bioenergy grasses. Theoretical and Applied Genetics, 2015, 128(1):1-14.
doi: 10.1007/s00122-014-2399-3 pmid: 25239219
[3] 刘宝玲, 张莉, 孙岩, 等. 谷子bZIP转录因子的全基因组鉴定及其在干旱和盐胁迫下的表达分析. 植物学报, 2016, 51(4):473-487.
doi: 10.11983/CBB15148
[4] 周汉章, 王新玉, 薄奎勇, 等. 夏谷田阔叶杂草密度与谷子产量损失关系的研究. 作物杂志, 2013(1):108-112.
[5] Dayan F E, Zaccaro M L D M. Chlorophyll fluorescence as a marker for herbicide mechanisms of action. Pesticide Biochemistry and Physiology, 2012, 102:189-197.
[6] Jimenez F, Fernandez P, Rojano-Delgado A M, et al. Resistance to imazamox in Clearfield soft wheat (Triticum aestivum L.). Crop Protection, 2015, 78:15-19.
[7] Reddy K N, Bellaloui N, Zablotowicz R M. Glyphosate effect on shikimate, nitrate reductase activity, yield, and seed composition in corn. Journal of Agricultural and Food Chemistry, 2010, 58(6):3646-3650.
doi: 10.1021/jf904121y pmid: 20180575
[8] Green J M. Review of glyphosate and als-inhibiting herbicide crop resistance and resistant weed management. Weed Technology, 2007, 21(2):547-558.
[9] Green J M, Owen M D K. Herbicide-resistant crops: Utilities and limitations for herbicide-resistant weed management. Journal of Agricultural and Food Chemistry, 2011, 59(11):5819-5829.
doi: 10.1021/jf101286h pmid: 20586458
[10] Green J M. The benefits of herbicide-resistant crops. Pest Management Science, 2012, 68(10):1323-1331.
doi: 10.1002/ps.3374 pmid: 22865693
[11] Breccia G, Gil M, Vega T, et al. Contribution of non-target-site resistance in imidazolinones-resistant Imisun sunflower. Bragantia, 2017, 76(4):536-542.
[12] Edwards R, Cole D J. Glutathione transferases in wheat (Triticum) species with activity toward fenoxaprop-ethyl and other herbicides. Pesticide Biochemistry and Physiology, 1996, 54:96-104.
[13] Hatton P J, Dixon D, Cole D J, et al. Glutathione transferase activity and herbicide selectivity in maize and associated weed species. Pest Management Science, 1996, 46:267-275.
[14] Cummins I, Wortley D J, Sabbadin F, et al. Key role for a glutathione transferase in multiple-herbicide resistance in grass weeds. Proceedings of the National Academy of Sciences of the United States of America, 2013, 110(15):5812-5817.
[15] Kebeish R, Azab E, Peterhaensel C, et al. Engineering the meta- bolism of the phenylurea herbicide chlortoluron in genetically modified Arabidopsis thaliana plants expressing the mammalian cytochrome P450 enzyme CYP1A2. Environmental Science and Pollution Research, 2014, 21:8224-8232.
[16] 宋慧, 王涛, 田礼新, 等. 谷子抗咪唑啉酮的遗传应用和基因初定位. 中国农学通报, 2021, 37(28):1-8.
doi: 10.11924/j.issn.1000-6850.casb2020-0749
[17] Martin M. Cutadapt removes adapter sequences from high- throughput sequencing reads. Embnet Journal, 2011, 17(1):10-12.
[18] Kim D, Langmead B, Salzberg S L. HISAT: a fast spliced aligner with low memory requirements. Nature Methods, 2015, 12(4):357-360.
doi: 10.1038/nmeth.3317 pmid: 25751142
[19] Kim D, Pertea G, Trapnell C, Pimentel H, et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, 2013, 14(4):36.
doi: 10.1186/gb-2013-14-4-r36 pmid: 23618408
[20] Livak K J, Schmittgen T D. Analysis of relative gene expression data using real-time quantitative PCR and the method. Methods in Molecular Biology, 2011, 25:402-408.
[21] Chen H, Saksa K, Zhao F, et al. Genetic analysis of pathway regulation for enhancing branched-chain amino acid biosynthesis in plants. Plant Journal, 2010, 63(4):573-583.
[22] Xing A, Last R L. A regulatory hierarchy of the arabidopsis branched-chain amino acid metabolic network. Plant Cell, 2017, 29(6):1480-1499.
[23] Ochogavía A C, Gil M, Picardi L, et al. Precision phenotyping of imidazolinones-induced chlorosis in sunflower. Breeding Science, 2014, 64:416-421.
doi: 10.1270/jsbbs.64.416 pmid: 25914598
[24] Balabanova D A, Paunov M, Goltsev V, et al. Photosynthetic performance of the imidazolinones resistant sunflower exposed to single and combined treatment by the herbicide imazamox and an amino acid extract. Frontiers in Plant Science, 2016, 7:1559.
pmid: 27826304
[25] Jez J M, Noel J P. A kaleidoscope of carotenoids. Nature Biotechnology, 2000, 18(8):825-826.
pmid: 10932147
[26] Kim B H, Kim S Y, Nam K H. Genes encoding plant-specific class III peroxidases are responsible for increased cold tolerance of the brassinosteroid-insensitive 1mutant. Molecules & Cells, 2012, 34(6):539-548.
[27] Hedtke B, Alawady A, Albacete A, et al. Deficiency in riboflavin biosynthesis affects tetrapyrrole biosynthesis in etiolated Arabidopsis tissue. Plant Molecular Biology, 2012, 78(1/2):77-93.
[28] Qin Y M, Hu CY, Pang Y, et al. Saturated very-long-chain fatty acids promote cotton fiber and Arabidopsis cell elongation. Plant Cell, 2007, 19(11):3692-3704.
[29] Denic V, Weissman J S. Molecular caliper mechanism for determining very-long chain fatty acid length. Cell, 2007, 130:663-677.
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